This invention relates generally to image reconstruction in computer tomography and more particularly relates to a software-based method for tracking organ motion and for motion correction.
In computer tomography, 2-D or 3-D image reconstruction is performed using projection data acquired over a period of time in a scan comprised of a series of projections. Each projection is a snapshot of a patient""s organs from a different angle, or perspective, and a scan typically includes hundreds of projections. Prior art methods used to reconstruct images from such data presume the patient and his organs are motionless during the entire scan such that a same fixed object is the subject of all acquired projections. Organ motion such as cardiac motion, blood flow, lung respiration or a patient""s restlessness during an acquisition process produces artifacts that appear as a blurring effect in the reconstructed image. Such blurring effects substantially complicate diagnosis or may even lead to inaccurate diagnosis putting the patient""s health at risk. Furthermore, repeating a scan in case of a complicated diagnosis due to blurring effects exposes the patient unnecessarily to radiation such as X-rays.
Speeding up data acquisition to reduce the blurring effects of organ motion is not possible with current x-ray tube technology. Therefore, signal processing algorithms accounting for organ motion have to be applied in the image reconstruction process.
Several techniques have been proposed to reduce the effects of organ motion. Srinivas, C. and Costa, M. H. M. in xe2x80x9cMotion-compensated CT image reconstructionxe2x80x9d, Proceedings of the IEEE Ultrasonics Symposium, 1, pp. 849-853, 1994, teach motion compensation using a linear model assuming translation and rotation. In U.S. Pat. No. 5,323,007 issued Jun. 21, 1994, Wernick et al. disclose a method for motion compensation using two projections of an object taken from different locations at different time instances. Organ motion is then measured from known image elements and an image is then corrected by solving a set of linear equations. Other techniques model organ motion as a periodic sequence and take projections at a particular point of the motion cycle or to correct image data using motion trajectories obtained from Fourier harmonics as disclosed in U.S. Pat. No. 5,615,677 to Pelc et al. issued Apr. 1, 1997. However, organ motion is too complex for these methods to substantially reduce the blurring effects and makes the prior art methods useful only in a very limited number of cases. In xe2x80x9cTomographic Reconstruction Of Time Varying Object From Linear Time-Sequential Sampled Projectionsxe2x80x9d, Proceedings of the IEEE, 0-7803-1775-0/94, pp. 309-312, 1994, Chiu, Y. H. and Yau, S. F. teach a method for compensating for organ motion by iteratively suppressing motion effects from the projections. This method reduces assumed spectral characteristics of the motion artifacts. The method depends on knowledge of at least some properties of the organ motion and requires a substantial number of iterations to converge, thereby requiring a large amount of computing time. In U.S. Pat. No. 5,671,263 issued Sep. 23, 1997, Ching-Ming discloses another spectral method for motion compensation. A high frequency signal of the organ motion is obtained using a high pass filter. The high frequency signal is then subtracted from the projection signal to remove motion artifacts. Unfortunately, removing high frequency components from the projection signal removes small size spatial structures from the image, as well.
In U.S. Pat. No. 5,806,521 issued Sep. 15, 1998, Morimoto et al. disclose a method for motion compensation based on correlating overlapping converted image data in an ultrasound imaging apparatus. In successive image frames a majority of information results from a same geometry. Due to this redundant information the data of two successive image frames is highly correlated. Organ motion between the acquisition of two frames will result in a shift of the correlation peak of the two frames with respect to each other corresponding to the amount of relative motion. Unfortunately, correlation of the two successive image frames taken from different spatial locations results only in a minor reduction of motion artifacts and, furthermore, may lead to cancellation of image details.
It is an object of the invention to provide a method for tracking organ motion and removing motion artifacts, which overcomes the aforementioned problems and substantially reduces motion artifacts in images of a large variety of CT scans.
It is further an object of the invention to provide a software-based method for tracking organ motion and removing motion artifacts for implementation in existing CT systems without major hardware modification.
In accordance with the invention, there is provided, a method of tracking motion present during computer tomography scan data acquisition of an object, the method comprising the steps of:
receiving a sensor time series indicative of image data of the object from a CT scanner;
providing the sensor time series to a processor; and,
using the processor, comparing image data of the object acquired from identical spatial locations at different times t and t+T to obtain information about the phase of the motion of the moving object and determining a sinogram indicative of the position of the object at the time instance each image is taken.
In accordance with the invention, there is provided, a method of motion correction in image data of computer tomography scans of an object comprising the steps of:
providing to a processor a sinogram indicative of the position of the object at the time instance each image is taken; and,
using the processor, determining motion corrected image data from the sinogram using retrospective gating.
In accordance with another aspect of the invention, there is provided, a method of motion correction in image data of computer tomography scans of an object comprising the steps of:
providing to a processor a sinogram indicative of the position of the object at the time instance each image is taken;
using the processor:
defining a phase of interest of the sinogram;
isolating every subsequent time instance during the data acquisition period when the object is again at the pre-selected phase of its motion cycle;
selecting a number of projections at each of the time instances;
assembling the projections into a phase coherent sinogram; and,
reconstructing an image of the object at the phase of interest based on the phase coherent sinogram.
In accordance with the invention, there is further provided, an image data processing system for tracking motion present during computer tomography scan data acquisition of an object, the system comprising:
port for receiving a sensor time series indicative of image data of the object from a CT scanner; and,
a processor for performing the steps of:
comparing image data of the object acquired from identical spatial locations at different times t and t+T to obtain information about the phase of the motion of the moving object; and,
determining a sinogram indicative of the position of the object at the time instance each image is taken.
In accordance with yet another aspect of the invention, there is provided, a method of generating a computer tomography motion picture of a moving object comprising the steps of:
providing to a processor a sinogram indicative of the position of the object at the time instance each image is taken;
using the processor:
defining a number of phases of interest of the sinogram, wherein the phases of interest are equally spaced over a single motion cycle of the object;
isolating every subsequent time instance during the data acquisition period when the object is again at the pre-selected phases of its motion cycle;
selecting a number of projections at each of the time instances;
assembling the projections into phase coherent sinograms; and,
reconstructing an image of the object at each of the phases of interest based on the phase coherent sinograms.